neuMF | This is our implementation for the paper | Recommender System library

by ngduyanhece Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | neuMF Summary

neuMF is a Python library typically used in Artificial Intelligence, Recommender System, Deep Learning, Pytorch applications. neuMF has no bugs, it has no vulnerabilities and it has low support. However neuMF build file is not available. You can download it from GitHub.

This is our implementation for the paper:. Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu and Tat-Seng Chua (2017). Neural Collaborative Filtering. In Proceedings of WWW '17, Perth, Australia, April 03-07, 2017. Three collaborative filtering models: Generalized Matrix Factorization (GMF), Multi-Layer Perceptron (MLP), and Neural Matrix Factorization (NeuMF). To target the models for implicit feedback and ranking task, we optimize them using log loss with negative sampling. Author: Dr. Xiangnan He (

Support

Quality

Security

License

Reuse

Support

neuMF has a low active ecosystem.

It has 15 star(s) with 7 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 345 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of neuMF is current.

Quality

neuMF has 0 bugs and 0 code smells.

Security

neuMF has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

neuMF code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

neuMF does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

neuMF releases are not available. You will need to build from source code and install.

neuMF has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 631 lines of code, 22 functions and 6 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed neuMF and discovered the below as its top functions. This is intended to give you an instant insight into neuMF implemented functionality, and help decide if they suit your requirements.

Evaluate a model
Evaluate a single rating
Calculate the CDG of a given rank
Gets the hit ratio of item in ranklist
Get an MLP model
Parse command line arguments
Load a pretraining model
Generate train instances

Get all kandi verified functions for this library.

neuMF Key Features

No Key Features are available at this moment for neuMF.

neuMF Examples and Code Snippets

No Code Snippets are available at this moment for neuMF.

Community Discussions

Trending Discussions on neuMF

No attribute 'compile', how can I modify the class, so that it works?

QUESTION

No attribute 'compile', how can I modify the class, so that it works?

Asked 2020-Oct-20 at 21:43

The neuMF class is not a Keras's class and therefore it doesn't provide any compile method. I would better use keras.Model instead of nn.Blocks.

Unfortunately, I do not really understand what nn.Blocks is and how I could replace it in the class. How should I modfy my code, so that it works with keras.Model and can use the Keras method?

Here is my code:

...

ANSWER

Answered 2020-Oct-20 at 21:43

After already quite some discussion in the comments, there are still several problems with your code and clarification needed from your side:

subclasses of keras.Model should implement the __call__ method, but not a forward method.
you can't just build numpy-operations like np.concatenate inside your model, always use keras-layers like tf.keras.layers.Concatenate.
as already commented, the error you've posted most likely comes from num_factors, num_users, num_items not being integer, though I can only guess here, since you did not provide those to us.
also, I can currently only guess what you are trying to achieve, since this is not at all clear from what you posted.

Let us approach the issues in a different way. The following code snippet runs without error and might be a good starting point for you:

Source https://stackoverflow.com/questions/64440377

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install neuMF

You can download it from GitHub.
You can use neuMF like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: